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Ai Data Labeling Jobs (NOW HIRING)

Aerotek

Data Labeling Specialist

San Jose, CA

$30/hr

🚀 Data Labeling Specialist - AI & Robotics 💡 No prior experience required -- All training will be provided Join our mission to build the world's first general-purpose humanoid robot. As a Data ...

Reducto

Data Labeling Lead (Contract)

Reducto is the agentic document platform for leading AI teams who demand enterprise performance at ... The Opportunity As Data Labeling Lead , you'll play a key role in leading and managing our in-house ...

Pareto AI

AI Engagement Manager

$150K - $180K/yr

Partner with Product, Delivery, and Engineering to design solutions for Agentic AI, data labeling, evaluation, RLHF, red-teaming, and emerging workflows * Ensure strong requirements gathering ...

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How much do ai data labeling jobs pay per hour?

As of Jun 6, 2026, the average hourly pay for ai data labeling in the United States is $47.27, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $69.95 per hour, depending on experience, location, and employer.

What is an AI Data Labeling job?

An AI Data Labeling job involves annotating or tagging data (such as images, text, audio, or video) to train machine learning models. Labelers categorize, classify, or highlight data based on specific guidelines to help AI understand patterns and make accurate predictions. This process is crucial for supervised learning, where models learn from labeled examples. AI Data Labeling jobs are common in industries like healthcare, finance, and autonomous vehicles. Attention to detail and consistency are key skills for success in this role.

What are the key skills and qualifications needed to thrive in the Ai Data Labeling position, and why are they important?

To thrive as an AI Data Labeling professional, you need strong attention to detail, analytical thinking, and the ability to follow precise guidelines, typically backed by a high school diploma or higher. Familiarity with annotation tools such as Labelbox, Supervisely, or internal labeling platforms, as well as basic understanding of data privacy practices, is often required. Patience, reliability, and good communication skills are important soft skills for consistently delivering high-quality labeled datasets and working effectively with team members. These skills ensure accurate data preparation for training AI models, directly impacting the model’s performance and the success of machine learning projects.

What are typical daily tasks for an AI Data Labeling professional?

As an AI Data Labeling professional, your primary responsibilities include reviewing raw images, audio, or text data and accurately tagging or classifying them based on set guidelines provided by your employer. You may also be required to flag ambiguous cases or data anomalies and provide feedback to improve labeling instructions. Collaboration with data scientists or machine learning engineers is common to ensure your work aligns with project needs. Maintaining high accuracy while meeting productivity goals is essential for success in this role.

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Ai Data Labeling jobs near you

AI Data Labeling & Quality Specialist

TPI Global (formerly Tech Providers, Inc.)

Fort Mill, SC • On-site

$15.50 - $20.25/hr

Full-time

Posted yesterday

Job description

Job Description
bilingual AI Data Labelling & Quality Specialist
3-6 Months possibility of conversion
Fort mill, SC (Remote role)
About the role:
  • We are seeking a bilingual AI Data Labelling & Quality Specialist to support the development of an AI-assisted sales system for our Home Services business.
  • This includes both a voice agent and tools for human sales agents, designed to deliver highly personalized customer journeys.
  • The ideal candidate will help improve our AI models by labelling ground-truth data, evaluating AI outputs, and providing structured feedback to enhance multilingual performance-in English and Spanish.

Responsibilities
  • Review, label, and categorize customer interaction data (audio and text) to create high-quality training datasets.
  • Evaluate AI/LLM outputs for accuracy, clarity, tone, and compliance with internal guidelines.
  • Provide detailed feedback to improve AI behaviors, dialog flows, and multilingual consistency.
  • Identify patterns, edge cases, and opportunities to increase the effectiveness of English and Spanish customer experiences.
  • Ensure data quality, confidentiality, and adherence to annotation standards.

Qualifications
  • Fluent in English and Spanish (spoken and written) with strong comprehension and communication skills.
  • Prior experience in data labelling, annotation, linguistics, QA, customer support, or AI training.
  • Familiarity with conversational AI, LLMs, or voice agents is a plus.
  • Strong attention to detail and ability to follow structured guidelines.
  • Comfortable working with productivity tools and web-based annotation platforms.
  • Ability to work independently, meet deadlines, and adapt to evolving requirements.

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Mohit Sharma

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